視頻地址：https://www.coursera.org/learn/ai-for-everyone/lecture/SRwLN/week-1-introduction
英文字幕：
Welcome to AI for everyone. AI is changing the way we work and live and this nontechnical course will teach you how to navigate the rise of AI. Whether you want to know what's behind the buzzwords or whether you want to perhaps use AI yourself either in a personal context or in a corporation or other organization, this course will teach you how. If you want to understand how AI is affecting society, and how you can navigate that, you also learn that from this course. In this first week, we'll start by cutting through the hype and giving you a realistic view of what AI really is. Let's get started. You've probably seen news articles about how much value AI is creating. According to a study by McKinsey Global Institute, AI is estimated to create an additional 13 trillion US dollars of value annually by the year 2030. Even though AI is already creating tremendous amounts of value into software industry, a lot of the value to be created in a future lies outside the software industry. In sectors such as retail, travel, transportation, automotive, materials, manufacturing and so on. I should have a hard time thinking of an industry that I don't think AI will have a huge impact on in the next several years. My friends and I used a challenge each other to name and industry where we don't think AI will have a huge impact. My best example was the hairdressing industry because we know how to use AI robotics to automate hairdressing. But, I once said this on stage and one of my friends who is a robotics professor was in the audience that day, and she actually stood up and she looked at me in the eye and she said, "You know Andrew, most people's hairstyles, I couldn't get a robot to cut their hair that way." But she looked at me and said, "Your hairstyle Andrew, that a robot can do." There is a lot of excitement but also a lot of unnecessary hype about AI. One of the reasons for this is because AI is actually two separate ideas. Almost all the progress we are seeing in the AI today is artificial narrow intelligence. These are AIs that do one thing such as a smart speaker or a self-driving car or AI to do web search or AI applications in farming or in a factory. These types of AI are one trick ponies but when you find the appropriate trick, this can be incredibly valuable. Unfortunately, AI also refers to a second concept of AGI or artificial general intelligence. That is the goal to build AI. They can do anything a human can do or maybe even be superintelligence and do even more things than any human can. I'm seeing tons of progress in ANI, artificial narrow intelligence and almost no progress to what AGI or artificial general intelligence. Both of these are worthy goals and unfortunately the rapid progress in ANI which is incredibly valuable, that has caused people to conclude that there's a lot of progress in AI, which is true. But that has caused people to falsely think that there might be a lot of progress in AGI as well which is leading to some irrational fears about evil clever robots coming over to take over humanity anytime now. I think AGI is an exciting goal for researchers to work on, but it'll take most for technological breakthroughs before we get there and it may be decades or hundreds of years or even thousands of years away. Given how far away AGI is, I think there is no need to unduly worry about it. In this week, you will learn what ANI can do and how to apply them to your problems. Later in this, course you'll also see some case studies of how ANI, this one trick ponies can be used to build really valuable applications such as smart speakers and self-driving cars. In this week, you will learn why this AI. You may have heard of machine learning and the next video will teach you what is machine learning. You also learn what is data and what types of data are valuable but also what does the data are not valuable. You learn what it is that makes a company an AI company or an AI first company so that perhaps you can start thinking if there are ways to improve your company or other organizations ability to use AI and importantly, you also learned this week what machine learning can and cannot do. In our society, newspapers as well as research papers tend to talk only about the success stories of machine learning and AI and we hardly ever see any failure stories because they just aren't as interesting to report on. But for you to have a realistic view of what AI and what machine learning can or cannot do, I think is important that you see examples of both so that you can make more accurate judgements about what you may and maybe should not try to use these technologies for. Finally, a lot of the recent rise of, machine learning has been driven through the rise of Deep Learning. Sometimes also called Neural Networks. In the final two optional videos of this week, you can also see an intuitive explanation of deep learning so that you will better understand what they can do particularly for a set of narrow ANI tasks. So, that's what you learn this week and by the end of this week, you have a sense of AI technologies and what they can and cannot do. In the second week, you'll learn how these AI technologies can be used to build valuable projects. You learn what it feels like to build an AI project as what as what you should do to make sure you select projects that are technically feasible as well as valuable to you or your business or other organization. After learning what it takes to build AI projects, in the third week you'll learn how to build AI in your company. In particular, if you want to take a few steps toward making your company good at AI, you see the AI transformation playbook and learn how to build AI teams and also built complex AI products. Finally, AI is having a huge impact on society. In a fourth and final week, you'll learn about how AI systems can be bias and how to diminish or eliminate such biases. You also learn how AI is affecting developing economies and how AI is affecting jobs and be better able to navigate this rise of AI for yourself and for your organization. By the end of this four recourse, you'll be more knowledgeable and better qualified than even the CEOs of most large companies in terms of your understanding of AI technology as well as your ability to help yourself or your company or other organization navigate the rise of AI as I hope that after this course, you'll be in a position to provide leadership to others as well as they navigate these issues. Now, one of the major technologies driving the recent rise of AI is Machine Learning. But what is Machine Learning? Let's take a look in the next video.
中文翻譯：
歡迎大家參加AI。人工智能正在改變我們的工作和生活方式，這個非技術課程將教你如何駕馭人工智能的興起。無論您是想知道流行語背後的內容，還是想在個人環境或公司或其他組織中自己使用AI，本課程都將教您如何操作。如果您想了解AI如何影響社會，以及如何進行導航，您還可以從本課程中學習。在第一週，我們將首先通過大肆宣傳，讓您真實地瞭解AI的真實情況。讓我們開始吧。您可能已經看過有關AI正在創造多少價值的新聞文章。根據麥肯錫全球研究所的一項研究，人工智能估計到2030年每年將創造額外的13萬億美元的價值。儘管人工智能已經爲軟件行業創造了巨大的價值，但還是要創造很多價值。在未來，軟件行業之外。在零售，旅遊，運輸，汽車，材料，製造等行業。我應該很難想到一個我不認爲人工智能將在未來幾年內產生巨大影響的行業。我和我的朋友們互相挑戰名稱和行業，我們認爲人工智能不會產生巨大的影響。我最好的例子是美髮行業，因爲我們知道如何使用AI機器人來自動化美髮。但是，我曾經在舞臺上說過這一天，我的一位機器人教授的朋友當天在觀衆席上，她實際上站起來，看着我的眼睛，她說，“你知道安德魯，大多數人的髮型，我無法讓機器人那樣剪頭髮。“但她看着我說，“你的髮型安德魯，一個機器人可以做的。”有很多令人興奮的事情，但也有很多關於AI的不必要的炒作。其中一個原因是因爲AI實際上是兩個獨立的想法。我們今天在AI中看到的幾乎所有進展都是人爲的狹隘智能。這些是能夠做一件事的AI，例如智能揚聲器或自動駕駛汽車或AI，用於在農業或工廠中進行網絡搜索或AI應用。這些類型的AI是一個小技巧，但是當你找到合適的技巧時，這可能是非常有價值的。不幸的是，AI也提到了AGI或人工一般智能的第二個概念。這是構建AI的目標。他們可以做人類可以做的任何事情，甚至可以做超級智能，甚至可以做任何比人類更多的事情。我在ANI中看到了很多進步，人工狹隘的情報以及幾乎沒有進展到AGI或人工智能。這兩個都是有價值的目標，不幸的是ANI的快速進展非常有價值，這使得人們得出結論認爲人工智能有很多進步，這是事實。但這導致人們錯誤地認爲AGI可能會有很多進展，這導致人們對邪惡聰明的機器人現在隨時接管人類的一些非理性擔憂。我認爲AGI對於研究人員而言是一個令人興奮的目標，但在我們到達之前它將需要大部分技術突破，它可能需要數十年，數百年甚至數千年才能實現。鑑於AGI有多遠，我認爲沒有必要過分擔心它。在本週，您將瞭解ANI可以做什麼以及如何將它們應用到您的問題中。在後面的課程中，您還將看到一些案例研究，瞭解ANI，這一招小馬可用於構建真正有價值的應用，如智能揚聲器和自動駕駛汽車。在這個星期，你將瞭解爲什麼這個AI。您可能聽說過機器學習，下一個視頻將教您什麼是機器學習。您還可以瞭解什麼是數據以及哪些類型的數據有價值，但也瞭解數據沒有價值。你瞭解到什麼使公司成爲人工智能公司或人工智能第一公司，這樣你或許可以開始思考是否有辦法改善你的公司或其他組織使用人工智能的能力，重要的是，你本週也學到了什麼機器學習可以也可以做不到。在我們的社會中，報紙和研究論文往往只談論機器學習和人工智能的成功故事，我們幾乎看不到任何失敗的故事，因爲它們報告的內容並不那麼有趣。但是爲了讓你對人工智能和機器學習能做什麼或不做什麼有一個現實的看法，我認爲重要的是你看到兩者的例子，這樣你就可以做出更準確的判斷，你可能不應該嘗試使用這些技術。最後，很多最近興起的機器學習都是通過深度學習的興起來推動的。有時也稱爲神經網絡。在本週的最後兩個可選視頻中，您還可以看到深度學習的直觀解釋，以便您更好地瞭解他們可以做些什麼，特別是對於一組狹窄的ANI任務。所以，這就是你在本週所學到的知識，到本週末，你對AI技術以及它們能做什麼和不能做什麼都有所瞭解。在第二週，您將學習如何使用這些AI技術來構建有價值的項目。您將瞭解構建AI項目的感受，以及確保您選擇技術上可行且對您或您的企業或其他組織有價值的項目。在瞭解了構建AI項目所需的內容之後，在第三週，您將學習如何在公司中構建AI。特別是，如果您想採取一些措施使您的公司擅長AI，您可以看到AI轉換手冊，並學習如何構建AI團隊以及構建複雜的AI產品。最後，人工智能正在對社會產生巨大影響。在第四周也是最後一週，您將瞭解AI系統如何偏向以及如何減少或消除此類偏差。您還將瞭解AI如何影響發展中經濟體以及AI如何影響工作，並且能夠更好地爲您自己和您的組織引導AI的這種崛起。在這四種資源的最後階段，您對大多數大型公司的首席執行官在理解人工智能技術方面以及幫助自己或公司或其他組織提升自身能力方面的能力方面，知識淵博，資質更高。因爲我希望在這個課程結束後，你能夠爲他人提供領導以及他們解決這些問題。現在，推動人工智能近期興起的主要技術之一是機器學習。但什麼是機器學習？我們來看看下一個視頻。